Selecting an Appropriate Metadata Standard
Selecting an appropriate metadata standard is partially dependent on how a user community
anticipates using the metadata to support their objectives. Metadata can be used for a range of
purposes including inventorying existing datasets, searching for and discovering datasets, proper
interpretation and use of data, and automation of data validation or analysis. Each of these uses
10 Metadata Guidance
requires increasing levels of detail in metadata (Table 1). Inventorying existing datasets may
only require a minimal set of metadata elements (e.g. a subset of CSDGM elements). The
CSDGM metadata standard supports search, discovery and distribution of datasets and supports
proper use of the data. This represents the most common use of metadata. Supporting the proper
interpretation and use of data requires description of the entities and attributes in the dataset.
These metadata elements are included in the Biological Data Profile. In addition to supporting
those activities, metadata can also be used to automate workflows by facilitating creation of data
entry applications, automation of data validation, exchange of data between data management
systems, and automation of metric creation. Supporting the automation of workflows can only be
accomplished through the use of detailed, machine-readable metadata. Data practitioners at the
National Center for Ecological Analysis and Synthesis (NCEAS) and the Long Term Ecological
Research Network (LTER) created the Ecological Metadata Language (EML) and have
demonstrated the potential for automation through the use of detailed, machine-readable
metadata.
See Table 1. Functional abilities of the major metadata standards
Organizations must evaluate their objectives for creating metadata and select metadata standards
with the appropriate level of detail to support those objectives. Given limited resources and tools
for metadata creation and varying objectives for how organizations use metadata, it is
recommended that organizations select metadata standards based on criteria including:
- relevance to organizational and regional monitoring objectives,
- duration of time since data creation, and
- desired level of automation.
Most organizations in the Pacific Northwest have large backlogs of data with limited or nonexisting
metadata. Completing an inventory of historic datasets using a metadata standard of
limited detail will help organizations prioritize historic datasets for further stewardship. For
selected datasets, metadata elements documented during the inventory stage can be
supplemented with additional elements to meet requirements of a more detailed standard.